Book Review: Claire Jowitt. <em>Voyage Drama and Gender Politics 1589-1642: Real and Imagined Worlds</em>. Manchester: Manchester University Press, 2003.
Bibliographic record
Abstract
circumstances, as in his dealings with Polonius, and Rosencrantz and Guildenstern.Did he not think he was killing the King when he killed Polonius?That too was a chance opportunity.Perhaps Hirsh becomes rather too confined by a rigorous logical analysis, and a literal reading of the texts he deals with.He tends to brush aside all alternatives with an appeal to a logical certainty that does not really exist.A dramatist like Shakespeare is always interested in the dramatic potential of the moment, and may not always be thinking in terms of plot.(But as I suggest above, the textual evidence from plot is ambiguous in the scene.)Perhaps the sentimentalisation of Hamlet's character (which the author rightly dwells on) is the cause for so many unlikely post-renaissance interpretations of this celebrated soliloquy.But logical rigour can only take us so far, and Hamlet, unlike Brutus, for example, does not think in logical, but emotional terms.'How all occasions do inform against me / And spur my dull revenge' he remarks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.114 | 0.106 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".